Advances in human respiratory organoid models for studying the pathogenesis and intervention strategies of COVID-19
Year: 2026
Type: article
Abstract: Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), affects multiple organ systems, with the respiratory system being the primary target. Respiratory organoids, which closely mimic the structure and function of the human respiratory tract, have emerged as essential tools for studying SARS-CoV-2 infection. This review summarizes current methods for generating various respiratory organoids, including nasal, tonsil, airway, bronchial, and alveolar organoids, and highlights their application in investigating the mechanism of SARS-CoV-2 infection and evaluating potential therapeutic agents. Meanwhile, this review also introduces respiratory organoid-on-a-chip technology, which can precisely regulate culture conditions and incorporate vascularization and immune cells to enhance physiological complexity, thereby providing crucial support for investigating SARS-CoV-2-induced lung injury, immune responses, and conducting high-throughput drug screening. The aim of this review is to provide valuable insights for further research into the pathogenesis and intervention strategies of COVID-19. • Respiratory organoids have emerged as essential tools for studying SARS-CoV-2 infection. • This review summarizes current methods for generating various respiratory organoids and highlights their application in investigating the mechanism of SARS-CoV-2 infection and evaluating potential therapeutic agents. • This review as also introduces respiratory organoid-on-a-chip technology, aiming to offer insights for further SARS-CoV-2 research.
Source: Virologica Sinica
Authors: Zeping Shan, Jiarui Li, Zihui Ye, Yuyue Chen, Jie Chen, Yuewen Chen, Xiaofan Wang, Chong Gao, Shibo Jiang, Naru Zhang
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $1,500
Awards: G5239942043, G6833891626
OpenAlex ID: W7127950086
